Delves into Big Data in neuroscience, analyzing large datasets and addressing challenges in data organization, standardization, integration, and visualization.
Introduces semantic modelling through tabular data and RDF, covering relational databases, schema migration, future-proof schemata, SPARQL querying, and metaknowledge limitations.
Explores the connection between physical theories and empirical data, contrasting standard quantum mechanics with Newtonian Mechanics' explicit ontology of particles in space.
Explores materials modelling, focusing on predicting and designing material properties through computation, including defect analysis, coherence time calculations, and quantum simulations.